ReAct Agent
Interleaves chain-of-thought Reasoning with Action execution, enabling LLMs to dynamically plan, act, and observe in a loop.
errorWhat Problem Does the ReAct Agent Pattern Solve?
Standard LLM prompting produces static responses without the ability to gather new information or take actions mid-generation. The model cannot verify its own claims, access external data, or adapt its approach based on intermediate results.
check_circleHow the ReAct Agent Pattern Works
Structure the agent into a Thought → Action → Observation loop. The LLM first reasons about what to do (Thought), then executes a tool or API call (Action), observes the result (Observation), and uses that to inform its next reasoning step. This continues until the task is complete.
ReAct Agent Pattern Architecture
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Implementation by Language
ReAct Agent Pattern in the Real World
“Like a detective investigating a case: they form a hypothesis (Thought), gather evidence by interviewing witnesses or examining clues (Action), analyze what they found (Observation), and then refine their theory. They keep investigating until they solve the case.”
Frequently Asked Questions
helpWhat is the difference between ReAct and Chain-of-Thought prompting?
Chain-of-Thought (CoT) prompting asks the model to reason step-by-step but does not involve external actions. ReAct extends CoT by interleaving reasoning with actual tool calls and observations, allowing the model to gather real-world information mid-reasoning.
helpHow do I prevent a ReAct agent from getting stuck in an infinite loop?
Set a maximum number of reasoning-action cycles (typically 5-10). Also include a 'give up' action that the agent can choose when it determines the task cannot be completed with available tools.
helpCan a ReAct agent use multiple tools in a single action step?
In the standard ReAct pattern, each action step uses one tool. However, parallel tool calling variants exist where the model can issue multiple tool calls simultaneously, which is supported by modern LLM APIs like Claude's tool use.